Such methods and devices find application especially in modern biology today. Especially for fluorescence microscopy, a number of specific fluorescence probes have been developed. These are suitable, for example, for specific labeling of antibodies, certain DNA sequences or other biological structures. Furthermore, they include fusion constructs of certain proteins with fluorescent proteins, such as GFP (Green Fluorescent Protein) or YFP (Yellow Fluorescent Protein), etc. Furthermore, special indicator dyes are included, the fluorescence of which is correlated with the concentration of certain ions, for example calcium, with respect to their intensity and/or emission spectrum.
Modern biology attempts to adjust the complexity of the measurement methods to the complexity of the investigated samples and thus many times it is interested in localizing as large a number of different markings in a sample as possible and to resolve these spatially from one another.
Another especially current problem is the quantitative determination of fluorophores which enter into interaction with one another through fluorescenceless [sic] energy transfer FRET (Fluorescence Resonance Energy Transfer). Such FRET-pairs consisting of donor and acceptor cannot be resolved from one another in an optical microscope. Rather, the superimposition of the donor and acceptor spectra or their relationship to one another is measured.
Another current problem is the separation of the fluorescence of an indicator dye into the portions of the bound and free form of the fluorophore for the purposes of obtaining the ratio and subsequent calculation of the activity of a ligand.
Another problem which occurs in almost all imaging fluorescence methods in biology is the consideration of the so-called autofluorescence, that is, the nonspecific background fluorescence which many structure exhibit, such as cells and substrate carriers.
In principle, an essential limitation of this method lies in the fact that the organic fluorophores that are usually used have relatively broad excitation and emission spectra which is attributed to the large number of phononic sublevels that participate in these organic molecules. Thus it becomes comparatively difficult to excite species of fluorophores contained in a sample in a specific way or to detect them specifically. Rather, usually one obtains a complex composition of the contributions of different species as signal.
Conventionally, the method employed is to use excitation channels which are as far away from each other as possible, and to employ as narrow detection channels as possible. The concept of excitation channel in this connection is understood to mean the sum of the properties of the light that excites the fluorescence. This includes especially the spectral properties which also includes in the framework of this description the intensity of the particular spectral components. In any case, other properties, such as the time of excitation and/or the duration of excitation combined as excitation time, can be used for the definition of an excitation channel. Analogously, here the concept of detection channel is defined as the sum of the properties of the elements which guide the fluorescent light emitted by the sample and filter and detect them. This includes again the spectral properties including the particular sensitivities toward the individual spectral components, and on the other hand the detection time, the detection time point and detection duration. Special combinations of excitation channels and detection channels are described below in a summarizing way as measurement channels.
In current practice, various methods are known which are aimed at optimum spectral resolution of the different types of fluorophores in the presence of one another and depend on the properties of the fluorophores and on their combination. Thus, for example, it is possible to carry out several recordings in succession with different excitation wavelengths in a given detection channel, where the excitation wavelengths are always chosen so that the absorption maximum of a fluorophore species is included as accurately as possible. In this case, one measurement channel is used per measurement. Another possibility consists in exciting the sample at an excitation wavelength which lies in the region of the excitation spectra of several fluorophore species and to divide the emitted light using filter sets or by cascades of beam splitters into spectral regions and then introduce these parts to separate photosensors. Thus, in this method, several measuring channels are used simultaneously. If the emission or excitation bands of the fluorophores of interest are sufficiently widely separated from one another, the frequency regions of the individual measurement channels can be chosen so that each channel corresponds to a fluorophore.
The disadvantage of these techniques is that mostly a certain cross-talk between the channels is unavoidable. This applies especially when a number of different fluorophores are used in a sample where the spectra overlap due to the limited bandwidth of usable wavelengths. Although this can be counteracted by sharply limiting the spectral limits of the individual detection channels, for example, by using narrow band pass filters, the consequence is that a large number of the fluorescence photons do not contribute to the signal, which has an adverse effect on the quality of the detected signal. This is especially undesirable because, due to bleaching processes of the fluorophores in the sample, the total number of photons that can be emitted by a given preparation is limited, but also because, due to photon noise, the quality and resolution of a measurement becomes better when more photons contribute to the measurement. Although almost all fluorescence photons can be made useful by breaking up the emitted fluorescent light spectrally and then treating the spectrum with the aid of a large number of spectral channels, the relative noise increases considerably in each individual extremely narrow channel, because only comparatively few photons are available for each individual channel, so that this method is only suitable in cases of application where the light intensity is especially high.
The problems addressed above can be reduced greatly when broad measurement channels are used, the cross-talk of which is deliberately taken into account and the received data are subjected to a considerable mathematical processing or evaluation. For this purpose, the received signals are converted in the detectors or in connected conversion units into digital data, and then these are stored in a memory unit of a digital data processing equipment. In many cases, for example in laser scanning microscopy (LSM), digitalization and subsequent processing of the data is an essential component of the technique.
The evaluation of the data mentioned above is usually done with the aid of a computer unit of the digital data processing equipment. Especially good results were obtained with the so-called “linear unmixing” method. This method is based on setting up and solving an inhomogeneous linear system of equations which, using the known properties of the measurement channels, establishes a relationship between the measured signal and the fluorophore composition in the sample. This system of equations can be represented mathematically in a matrix representation as{right arrow over (y)}=A{right arrow over (B)}+{right arrow over (I)}·{right arrow over (b)}  (1)or in a component representation
                              y          r                =                                            ∑                              μ                =                1                            p                        ⁢                                          I                r                            ⁢                              a                                  μ                  ⁢                                                                          ⁢                  r                                            ⁢                              B                μ                                              +                                    I              r                        ⁢                          b              r                                                          (        2        )            
These formulas are to be understood as follows: The vector {right arrow over (B)} represents the different species of fluorophores in their relative concentration at a given image point. Let p be the number of different fluorophore species. Thus, the vector {right arrow over (B)} has p components Bμ. The vector {right arrow over (y)} represents the signal detected in each measurement channel. Let q be the number of measurement channels. Thus, the vector {right arrow over (y)} has q yr components. For example, if four different excitation wavelengths and four different spectral detection windows were used, the number of measurement channels is q=16. The vector {right arrow over (I)} represents the excitation intensity used for each measurement channel and thus has q components Ir. The matrix A is the coefficient matrix which links the chemical composition {right arrow over (B)} of the fluorophores through the excitation intensities Ir of the excitation channels and the other properties aμr of the measurement channels to the resulting signal {right arrow over (y)}. Thus, the matrix A has pq elements Iraμr. Finally, the vector {right arrow over (b)} with q components br is a correction quantity which represents the scattered light or another background light in each measurement channel. The quantities Bμare usually to be regarded as location dependent, while the other quantities on the right side of equations (1) and (2) represent parameters which are normally the same for all pixels. Autofluorescence of the measured object can be treated either as fluorescence of an additional fluorophore Bμor as background light br (in case it is location independent). In the case of FRET, an FRET-pair can be considered as an independent chromophore, the concentration of which is given through one of the quantities Bμ.
The goal of“linear unmixing” is to find the solution B of the above linear system of equations, which is possible mathematically by simple inversion of the coefficient matrix A as long as the number of equations q is greater than or equal to the number of different fluorophore species p. For the algorithmic conversion of this mathematical operation, a number of numerical methods are known to the person skilled in the art. An explanation of this technique is given in Farkas et al.: “Non-invasive image acquisition and advanced processing in optical bio-imaging”, Computerized Medical Imaging and Graphics, 22 (1998), p. 89-102 or Dickinson et al.: “Multi-spectral imaging and linear unmixing at whole new dimension to laser scanning fluorescent microscopy”, BioTechnics, 31, No. 6 (2001), p. 1272-1278 as well as Boardman: “Inversion of imaging spectroscopy data using singular value decomposition”, Proc. IGARSS, 89, No. 4 (1989), p. 2069-2072. An implementation of this method of evaluation in LSM device was realized by the company Carl Ziess, Jena, Germany, in their Laser-Scanning-Microscope LSM 510 meta.
As explained, the method of linear unmixing represents a proven means of data evaluation when knowing the properties of the measurement channels used. However, a disadvantage is that the selection of suitable measurement channels, that is, the adjustment of all parameters, such as excitation wavelength, excitation intensity, excitation time and detection wavelength and detection time is left to the intuition of the user, as before. However, since intuition is guided by concrete rules which are obvious to the user, as before, if possible, a fluorophore species should be assigned to each measurement channel so that the possibilities provided by complex data analysis are usually not utilized.